Measuring the concentration of substances, particularly in the presence of other, confounding substances (“interferents”), is important in many fields, and especially in medical diagnosis and disease management. For example, the measurement of glucose in bodily fluids, such as blood, is crucial to the effective treatment of diabetes.
Multiple methods are known for measuring the concentration of analytes such as glucose in a blood sample. Such methods typically fall into one of two categories: optical methods and electrochemical methods. Optical methods generally involve absorbance, reflectance or laser spectroscopy to observe the spectrum shift in the fluid caused by the concentration of the analytes, typically in conjunction with a reagent that produces a known color when combined with the analyte. Electrochemical methods generally rely upon the correlation between a charge-transfer or charge-movement property of the blood sample (e.g., current, interfacial potential, impedance, conductance, and the like) and the concentration of the analyte, typically in conjunction with a reagent that produces or modifies charge-carriers when combined with the analyte. See, for example, U.S. Pat. Nos. 4,919,770 to Preidel, et al., and 6,054,039 to Shieh, which are incorporated by reference herein in their entireties.
An important limitation of electrochemical methods of measuring the concentration of a chemical in blood is the effect of confounding variables on the impedance of a blood sample. For example, the geometry of the blood sample must correspond closely to that upon which the impedance-to-concentration mapping function is based.
The geometry of the blood sample is typically controlled by a sample-receiving chamber of the testing apparatus in which the fluid sample is received and held during its analysis. In the case of blood glucose meters, for example, the blood sample is typically placed onto a disposable test strip or biosensor that plugs into the meter. The test strip may have a sample chamber to define the geometry of the sample. Alternatively, the effects of sample geometry may be limited by assuring an effectively infinite sample size. For example, the electrodes used for measuring the analyte may be spaced closely enough so that a drop of blood on the test strip extends substantially beyond the electrodes in all directions. Regardless of the strategy used to control sample geometry, typically one or more dose sufficiency electrodes are used to assure that a sufficient amount of sample has been introduced into the sample receiving chamber to assure an accurate test result.
Other examples of limitations to the accuracy of blood glucose measurements include variations in blood chemistry (other than the analyte of interest being measured). For example, variations in hematocrit (concentration of red blood cells) or in the concentration of other chemicals, constituents or formed elements in the blood, may affect the measurement. Variation in the temperature of blood samples is yet another example of a confounding variable in measuring blood chemistry. In addition, certain other chemicals can influence the transfer of charge carriers through a blood sample, including, for example, uric acid, bilirubin, and oxygen, thereby causing error in the measurement of glucose.
Efforts to improve test strips have been mainly directed to making them smaller, faster, and require less sample volume. For example, it is desirable for electrochemical biosensors to be able to analyze as small a sample as possible, and it is therefore necessary to minimize the size of their parts, including the electrodes. Traditionally, screen-printing, laser scribing, and photolithography techniques have been used to form miniaturized electrodes. These methods are undesirably time-consuming, however, and screen-printing or laser scribing technologies pose limitations on the edge quality of the electrical patterns formed, such that gap widths between electrical elements normally must be 75 microns or more. Further, some of these techniques make it unworkable on a commercial scale to remove more than a small fraction, e.g., more than 5-10% of the conductive material from a substrate to form an electrical pattern.
The electrode structures in available electrochemical test strips made by these techniques typically have one or perhaps two pairs of electrodes, and the measurements obtained by these electrode structures are quite sensitive to the interferents discussed above. Thus, the signal produced by the analyte desired to be analyzed must be deconvoluted from the noise produced by the interfering substances. Many approaches have been employed to attenuate/mitigate interference or to otherwise compensate or correct a measured value. Often, multiple design solutions are employed to adequately compensate for the sensitivities associated with the chosen measurement method.
One approach involves removing interfering materials such as blood cells from the fluid sample before it reaches the electrodes by using perm-selective and/or size-selective membranes, filters or coatings. Multiple layers of membranes are often laminated together to achieve the ultimate goal of delivering a fluid to the electrodes which contains only low levels of interferents. Unfortunately, however, this approach suffers from incremental costs of goods, viz., coatings and membranes that must often be pre-treated prior to assembly. It also incurs additional manufacturing process steps that further increase manufacturing cost and complexity while decreasing the speed of manufacture. This approach addresses the attenuation problem by increasing the complexity and cost of the test strip, thereby reducing the burden of the meter which reads the strips.
Another general approach involves the use of sophisticated excitation and signal processing methods coupled with co-optimized algorithms. While simpler, less complex test strip architectures and manufacturing processes may be realized, instrumentation costs, memory and processor requirements, associated complex coding, and calibrated manufacturing techniques are all increased by this approach. Systems employing this approach address the attenuation problem by placing a higher computational burden on the meter that reads the strips.
Yet another more recent approach involves neither the strip nor instrumentation, per se, but rather exploits the measurement methodology. An example of this approach is the use of a coulometric method to attenuate the influence of hematocrit and temperature. This coulometric approach, however, requires a tight manufacturing tolerance on the volume of the sample receiving chamber in the test strips produced, since the entire sample is used during the analysis. Additionally, commercially available test strips using this technology require two separate substrates printed with electrodes, which further increases manufacturing costs. The requirement that much of the sample volume be interrogated may also limit test speed. Further, this approach requires relatively large electrodes to provide significant electrolysis of the sample in a relatively short time in order to estimate the “endpoint” of the coulometric detection.
It is also well known to those skilled in the art that all of the above approaches are further supported by the initial design of reagent systems. In the detection of glucose, for example, this may involve the use of selective redox mediators and enzymes to overcome the detrimental influence of redox-active species or the presence of other sugars.
It would be desirable to provide a simpler, less costly method for attenuating the influence of interferents, in a manner that does not suffer the demerits associated with the general approaches currently in wide use. It would also be desirable to provide a more functional, robust and user-friendly system for analyzing fluid samples, but without increasing the costs.